Learn the data skills necessary for turning large sequencing
datasets into reproducible and robust biological findings. With
this practical guide, you'll learn how to use freely available open
source tools to extract meaning from large complex biological data
sets. At no other point in human history has our ability to
understand life's complexities been so dependent on our skills to
work with and analyze data. This intermediate-level book teaches
the general computational and data skills you need to analyze
biological data. If you have experience with a scripting language
like Python, you're ready to get started. Go from handling small
problems with messy scripts to tackling large problems with clever
methods and tools Process bioinformatics data with powerful Unix
pipelines and data tools Learn how to use exploratory data analysis
techniques in the R language Use efficient methods to work with
genomic range data and range operations Work with common genomics
data file formats like FASTA, FASTQ, SAM, and BAM Manage your
bioinformatics project with the Git version control system Tackle
tedious data processing tasks with with Bash scripts and Makefiles
General
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